磨料水射流切割质量的参数化模型

作为一种新型的冷态高能束切割技术,磨料水射流(AWJ)以其独特的优点得以广泛应用,但其本身的技术特性使得切割质量存在不足。本文从能量角度分析了AWJ切割质量的影响因素,结合实验数据采用回归分析方法建立了AWJ切割质量与工作压力、切割速度、磨料流量的半经验模型,能够可以满足工程需要。为AWJ切割工艺参数优化选择及切割质量的评价、分析提供了理论基础。     

磨料水射流切割工艺参数的确定

磨料水射流(AWJ)切割加工在现代制造业中已得到广泛应用，AWJ本身的技术特性使得切割断面和切缝质量存在不足。为实现AWJ精确、高效切割，分析了射流、钻孔、切割及工件等AWJ切割工艺参数，并对直线段和曲线段切割速度确定方法进行了探讨。     

磨料水射流的切割机制

研究了100MPa～400MPa高水压下磨料水射流（AWJ）的切割机制。根据射流与材料之间的相互作用过程,建立和验证了AWJ切割过程模型。揭示了典型材料的切割特征（切割深度、切口宽度和冲蚀量）与切割变量（水压、靶距和切割速度等）的相关规律,以及磨料、材质两大因素的影响。获得了结果对AWJ切割技术的开发和应用具有指导意义和实用价值。     

磨料水射流切割断面质量的研究

磨料水射流(AWJ)在难加工材料切割中得到广泛应用，但由于切割断面存在斜条纹限制了AWJ的应用。研究了射流压力和切割速度对塑性和脆性材料切割断面质量的影响规律，通过对AWJ切割机理和切割过程的分析，探讨了AWJ切割断面的形貌特征及其形成机理，认为是射流断面磨料动能的分布不均和射流的偏转滞后造成了AWJ切割断面斜条纹和曲线及尖角处的尖端，可以通过喷头摆动进给和切割速度补偿两种控制设计方案来实现AWJ的高效切割。     

磨料水射流切割钛合金材料的试验研究北大核心CSCD

针对传统工艺对钛合金等难加工材料切割存在诸多弊端的问题,应用磨料水射流(AWJ)技术切割难加工材料可以有效避免工件温度积聚及刀具损伤等,在非淹没条件下对钛合金材料进行切割加工,通过正交试验法对试验结果进行分析,得出水射流压力、靶距及喷嘴移动速度在切割过程中的影响权重,并对3个加工参数进行排序,优化出最佳加工参数组合为A_(3)=280 MPa、C_(1)=10 mm、B_(1)=200 mm/min。试验表明,AWJ技术可显著提高材料的去除率,有利于钻屑的回收利用。对切割过程中的几何因素、动力学特性及材料物理性质进行量纲分析,依据相似第二定律(π定理)建立磨料水射流切割深度与各因素之间的无量纲函数关系式,给出各影响参数的耦合关联性。分析磨料水射流切割钛合金材料最优参数,对磨料水射流技术应用于切割难加工材料有一定的实际意义。     

预测磨料水射流切割质量模型的研究

磨料水射流(AWJ)是高速水与磨料混合对材料进行加工的一种新型冷态高能切割技术,有着广阔的应用前景。但因其流态的特性,使得切割质量存在一些缺陷。为了提高工件表面质量和生产效率,在优化选择切割工艺参数组合的基础上,获得大量实验数据,试图建立能够精确预测切割质量的网络模型。通过程序对模型拓扑结构的改进,使得模型预测的切割质量更准确,很好地满足加工需要。     

超高压磨料水射流切割质量的实验研究

对磨料水射流切割断面的形貌特征及其形成机理进行了分析.针对国产AWJ切割系统的特点,实验研究了系统主要参数对几种常用材料切割质量的影响规律.分析了塑性和脆性材料的切割断面特点,为实际的工艺参数选择提供了可靠依据.     

蜂窝复合材料超声切割力建模及工艺参数选择研究

针对Nomex蜂窝复合材料超声切割加工因缺乏系统化的理论指导以及工艺参数选择的盲目性而导致导致工件加工质量差的问题,对蜂窝复合材料直刃刀超声切割力以及工艺参数的选择进行了研究,基于刀具运动学特性分析建立了超声切割力与工艺参数的关系理论模型。基于该模型,研究了施加超声波振动能量后引起切割力变化情况,基于该模型,通过运用Matlab软件仿真分析,研究了工艺参数对超声切割力的影响规律。研究结果表明,与普通加工相比,采用超声复合切割蜂窝复合材料可以有效地降低切割力。刀尖角、刀刃面夹角对切割力的影响较为显著,其次是前倾角,刀具摆角对切割力的影响最小,该结果为工艺合理选择及进一步优化奠定了较好的理论基础。     

基于多种代理模型的光纤激光切割质量预测

为了提高光纤激光切割质量的预测精度,分别使用了多项式响应面法、克里金法和支持向量回归法三种代理模型方法,建立了激光功率、切割速率和辅助气体压力等加工参数与挂渣量之间的预测模型。使用拉丁超立方抽样法产生30组训练数据,利用正交试验法产生25组验证数据用以验证预测模型的精度。结果表明,利用克里金法和支持向量回归法建立的模型均成功地预测了挂渣质量,其中克里金法建立的模型预测精度最高,并利用该模型分析了激光切割加工参数对挂渣量的影响规律。     

应用模糊理论预测磨料水射流切深模型的建立

以理论为基础,应用磨料水射流切割加工时的工艺参数:水射流压力、射流横移速度和磨料流量等实验数据,建立一个模糊控制模型。这个模糊控制模型可以预测在任何给定一组加工参数时,可获得的切割深度。给出磨料水射流切割铝合金实例。     

磨料水射流切割质量的神经网络预测

磨料水射流切割质量影响因素较多,难以建立有效的理论模型,结合实验结果,建立磨料水射流切割质量的神经网络预测模型。结果表明,对于所给定切割参数,该模型能快速、准确、可靠地预测出切割质量。     

An adaptive control strategy for the abrasive waterjet cutting process with the integration of vision-based monitoring and a neuro-genetic control strategy

This paper presents an integrated approach for the monitoring and control of abrasive waterjet (AWJ) cutting process. A machine-vision-based monitoring approach was proposed to obtain the bore diameter of the focusing nozzle from time to time. A neuro-genetic approach, proposed by Srinivasu and Ramesh Babu (Appl Soft Comput 8(1):809–819, 2008) was employed as a control strategy to modify the process parameters, such as water pressure, abrasive flow rate, and jet traverse rate, so as to maintain the desired depth of cut, with changes in the diameter of the focusing nozzle monitored with a machine vision system. By combining the monitoring and control strategies, an integrated approach for adaptive control of AWJ cutting process is realized. The effectiveness of the proposed integrated approach for adaptive control of AWJ cutting process was shown by comparing the results obtained from the experiments with the process parameters suggested by the control strategy to achieve the desired depth of cut. From the results of the study, it is seen that the proposed monitoring system is capable of monitoring the focusing nozzle diameter with a mean absolute deviation of 0.05 mm and that the neuro-genetic strategy is capable of modifying the controllable process parameters to maintain the desired depth of cut with a mean absolute deviation of 0.87 mm.     

ENHANCING THE DEPTH OF CUT IN ABRASIVE WATERJET CUTTING OF ALUMINA CERAMICS BY USING MULTIPASS CUTTING WITH NOZZLE OSCILLATION

An experimental investigation is presented to increase the depth of cut in abrasive waterjet (AWJ) cutting of alumina ceramics by introducing a new cutting technique combining multipass operations with controlled nozzle oscillation. Plausible trends of the depth of cut per pass and total depth of cut with respect to the number of passes and the parameters in each pass are discussed. It shows that cutting with nozzle oscillation can significantly increase the depth of cut in the single-pass cutting mode, while further gains in the depth of cut can be made by using multipass cutting with nozzle oscillation. While multipass cutting can be used to increase the total depth of cut for machining thicker materials, it has been found that an average increase of 50.8% in the total depth of cut can be expected by using multipass cutting with nozzle oscillation as compared to single-pass cutting without nozzle oscillation within the same cutting time. Recommendations are finally made as a practical guide for the selection of process parameters in multipass AWJ cutting of alumina ceramics with controlled nozzle oscillation.     

Optimization of abrasive waterjet machining using multi-objective cuckoo search algorithm

Abrasive waterjet (AWJ) machining is widely applied in the fields of civil and mechanical engineering. In this study, a general and theoretical analysis procedure was presented before computing application. It mainly focused on the kinetic energy model and wear rate model in machining process. Then, the multi-objective cuckoo algorithm was employed for optimization design of AWJ cutting head model, making sure to maximize the output energy and minimize the nozzle erosion rate while keeping the other factors constant. To demonstrate the effectiveness of the above strategy, a practical AWJ machining system was selected for investigation purpose. The proposed model was compared with experimental data for investigating the difference between the initial design and the optimized model. The results showed that the multi-objective cuckoo algorithm has great ability in prediction of outlet power and wear rate. Meanwhile, the optimized parameters were also superior to the original design, compared with experimental test data. The developed model can be used as a systematic approach for prediction in an advanced manufacturing process.     

不同金属材料在磨料水射流加工时的可加工性的试验研究

通过对磨料水射流切割金属材料过程的能量转移过程的分析,并且将粉碎原理中的比表面能的理论引入切割深度的分析。得出了不同金属材料被切割时由于比表面能的不同,在相同的切割参数的情况下达到相同切割深度时候的切割速度不同。并且通过试验加以验证,同时得出316不锈钢和6061铝合金板材切割时的可加工性特征系数。该系数可以很好的用于磨料水射流切割时候的参数设定。     

An investigation of the hole machining processes on woven carbon-fiber reinforced polymers (CFRPs) using abrasive waterjets

An investigation of the hole cutting and drilling processes on woven carbon-fiber reinforced polymer sheets using abrasive waterjet (AWJ) is presented. The drilling process uses a stationary AWJ to impinge a target material to make a hole, while the cutting process requires an AWJ to penetrate the workpiece before moving in a circular path to cut a hole. It is found that the holes machined by both the processes exhibit similar geometrical features, where the diameter at the top is greater than at the bottom. It is further found that the holes from the drilling process have a better roundness than those from cutting process primarily due to the jet instability during cutting movement. Plausible trends of the hole characteristics (e.g., diameter and wall inclination) and defects (e.g., delamination) with respect to the process parameters are discussed. It is shown that water pressure is the major parameter affecting hole defects. The hole drilling process yields more severe defects than the cutting process because of the initial impact of the jet. Predictive models for machined hole diameter in both processes are developed. The model predictions are in good agreement with the experimental data under the corresponding conditions.     

An exploration of an abrasive water jet cutting front profile

Abrasive water jet (AWJ) now is used as a precision cutting tool. With this tool, dimension tolerance less than 0.1 mm is expected in the cutting process. This dimension tolerance is enough for some applications. However, higher precision is necessary in order to use AWJ in some other applications. To get higher precision in an AWJ cutting process, controlling AWJ beam more accurately is needed, and this further leads to understanding AWJ cutting front more accurately. This paper compared the current cutting front profile exploration methods and then provided a new method to collect AWJ cutting front information accurately. With this new method, a better understanding of the cutting front profile is possible, which further leads to higher precision cutting of AWJ. This paper also demonstrated that the AWJ cutting front profile could be fitted by parabolic curves accurately.     

A key parameter to characterize the kerf profile error generated by abrasive water-jet

As the only cold high-energy beam machining technology, abrasive water-jet (AWJ) is one of the most rapidly developed techniques in material manufacturing industry. However, the application of AWJ is limited by the cutting accuracy it can achieve. Kerf profile generated by AWJ is different as the cutting parameters change. As a result, it has become a major factor which affects the cutting accuracy when AWJ is used as a machining tool. Researchers used taper error to characterize kerf profile error generated by AWJ in the past years. And many efforts have been put on how to eliminate taper error by using a tilting cutting head of a 5-axis AWJ machine. However, using taper error to characterize the kerf profile error generated by AWJ is not accurate since kerf profile error might appear in different styles. And using a 5-axis AWJ machine to eliminate taper error is only effective in some special cases. To effectively eliminate taper error, the first thing needs to do is to find out whether the kerf profile error can be compensated or not. Based on research, a key parameter, named kerf profile coefficient O, which can be used to characterize kerf profile error and further to guide people to use different ways to compensate kerf profile error, has been defined in this paper. To further illustrate the efficiency of this coefficient, a series of cutting experiments have been carried out and the experimental results have been discussed.